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The question whether representation of travel experience actually leads to personal prestige enhancement has been widely neglected so far. The study of prestige benefits of travel is a necessary endeavour to develop suitable methodological approaches toward the concept, in order to close critical knowledge gaps and enhance scientific understanding. The present thesis lays out the rationale and results of three research projects which shed light onto the relationship between touristic self-presentation and its effects on personal prestige evaluations of the social environment. The empirical studies conclude in the following main findings: (1) Leisure travel is a useful means for people to self-express in a positive way, and material representations of travel are frequently displayed to others. Tourists make use of travel experience to self-present in a positive way by uploading photos on social media, collecting and displaying souvenirs, wearing jewellery and clothing from their last trip, or talking about their trips to others. They express positive self-messages about personal character traits, affiliation to social in-groups and proof of having travelled somewhere. The findings ascertain the utility of travel representations for positive self-expression, showing that travel experience is an effective vehicle for conspicuous consumption and self-expression as an antecedent for personal prestige enhancement. (2) Personal prestige is an element of social relations, and holds capacity to affect perceptions of social inclusion and social distinction, so it has to be conceptualised as a multidimensional construct. In a tourism context, personal prestige is reliably measurable along the four dimensions of hedonism, social inclusion, social distinction and prosperity. The herein developed Personal Prestige Inventory (PPI) is a valid, reliable and parsimonious measurement tool which substantially enhances methodological approaches toward empirical research into personal prestige. (3) The way in which people represent travel experience to others measurably affects how their personal prestige is evaluated by social others. Empirical evidence of a series of experimental studies provides support for the assumption that representation of travel experience has an effect on the social evaluation of tourists' personal prestige. Experimental variance suggests small to moderate effects on personal prestige depending on the amount of leisure information given about a person, participation in tourism, and the destination and type of travel represented. This evidence is reasonable basis to conclude that whether and how people travel, and whether and how they share travel experience with others, does measurably affect social other's evaluation of their personal prestige.
Destination websites, which are maintained by destination marketing/management organisations (DMOs), are a key source of information for tourists in the pre-trip phase. DMOs are increasingly applying experiential marketing on their websites to support positive pre-travel online destination experiences (ODEs) and make the vision of the holiday as vivid as possible. However, research into technology-driven travel experiences is still in its infancy. In particular, a theoretical understanding of the nature of ODEs arising from destination websites is still lacking. Therefore, this dissertation is dedicated to an extensive investigation of ODEs on destination websites in the pre-travel phase. The aims were to analyse the influences of experiential design on ODEs, explore the ODE dimensions, and develop and validate a measurement tool for assessing the ODE values of destination websites. In the first qualitative multi-method study (eye-tracking, retrospective think-aloud protocols, semi-structured interviews, and video observations), the objective was to gain an in-depth understanding of the ODE facets in the travel inspiration phase. It was found that the experience dimensions adopted in previous research regarding the product-brand context (sensory, affective, intellectual, social, and behavioural dimensions) also occurred in the ODE context but exhibited some particularities, such as a future-oriented affective component (affective forecasting). Moreover, a supplementary spatio-temporal experience dimension was identified. An online field experiment was subsequently conducted and aimed at assessing the effects of applying experiential marketing on destination websites on ODEs in the travel inspiration phase. Based on the findings of Study 1, an initial attempt at developing an ODE measurement instrument was made and the ODE dimensionality tested. The results showed the theoretically relevant experience dimensions to be less differentiated compared to the product-brand context; instead, they merged into a holistic ODE encompassing several experience facets. Furthermore, it was shown that the application of experiential design enhanced ODEs; however, considering the subjectivity of experiences, the effect was rather small. Accordingly, complex multi-media elements do not automatically increase the experiential effect. In the third study, a quasi-online field experiment was conducted, simulating the travel information phase (higher involvement than Study 2) to re-assess the ODE dimensions and develop and validate a measurement instrument. The results showed the overall ODE to be reflected by two interrelated dimensions that aligned with the dual process theory: hedonic and utilitarian experiences. The facets identified in the first study were largely reflected in these two overarching components. Moreover, a reliable, valid, and parsimonious second-order measure for assessing ODEs was proposed. Overall, the results yielded by this dissertation enhance the scientific understanding of the technology-empowered tourist experience in the currently under-researched pre-travel experience phase. In addition, by proposing a new scale for the measurement of ODEs, this dissertation provides useful methodological advancements that can pave the way for further research in this field.
The doctoral dissertation deals with the problems of the diagnosis of rolling bearings using recurrence analysis. The main topic is the influence of radial internal clearance on the change of dynamics in a self-aligning double-row ball bearing with a tapered bore, in which the axial preload can control this parameter in a wide range. The dissertation began with an analysis of the state of knowledge. In the next part of the dissertation, the thesis was formulated and activities related to its proving were defined. The theoretical part was supplemented with the basics related to vibroacoustic diagnostics of rolling bearings and presented methods that can be used for their diagnostics. The research on proving the thesis was started with the preparation of a mathematical model in which a change in the damping coefficient in the field of radial clearance was adopted, a difference in the clearance value for a given row of balls was proposed, and the influence of shape errors and radial shaft endplay on the dynamics of the tested bearing was taken into account. During the dynamics tests, the radial clearance was adopted as a bifurcation parameter, and on the basis of the bifurcation diagram, it was possible to indicate the characteristic areas of bearing operation due to the radial internal clearance. In order to verify the model, experimental tests were carried out with a series of bearings in which the radial clearance was changed in a wide range possible to be physically realized. Recurrence analysis was used for both the dynamic response obtained from model and experimental studies. Owing to the comparative analysis of the dynamic response, recurrence quantificators were selected that are most susceptible to changes in radial clearance to bearing dynamics. Moreover, as a result of the research, it was possible to select a narrow range of radial clearance, ensuring the smoothest operation of the tested bearing.
This doctoral thesis deals with the topic of organizational misconduct and covers the three salient research streams in this area by addressing its performance outcomes, antecedents, and preventive measures. Specifically, it is concerned with the question of how different forms of misconduct are reflected in the stock performance of related organizations, thereby, covering the three pillars of corporate sustainability environmental, social, and governance (ESG). Furthermore, it aims to conceptualize how individual cognitive biases may lead to misconduct, therefore, potentially representing an antecedent and how existing management control systems can be enhanced to effectively address specific forms of misconduct, respectively. To these ends, the author first reviews the research stream of stock price reactions to environmental pollution events in terms of the underlying research samples, methodological specifications, and theoretical underpinnings. Based on the findings of the systematic literature review (SLR), he performs three stock-based event studies of the Volkswagen diesel emissions scandal (Dieselgate), workplace sexual harassment (#MeToo accusations), and the 2003 blackout in the US to cover the three ESG dimensions, respectively. In line with the SLR, his event studies reveal substantial stock losses to firms involved in misconduct that are eventually even accompanied by a spillover effect to uninvolved bystanders. Then, the author reviews the extant literature conceptually to develop a framework outlining how moral licensing as an individual cognitive bias might lead to a self-attribution of corporate sustainability, a consecutive accumulation of moral credit, and a later exchange of this credit by engaging in misconduct afterward. Finally, he assesses existing workplace sexual harassment management controls, such as awareness training and grievance procedures critically in another conceptual analysis. Based on the shortcomings stemming from management controls' focus on compliance and negligence of moral duties, he introduces five specific nudges firms should consider to enhance their existing management controls and eventually prevent occurrences of workplace sexual harassment. Based on the six distinct articles within this doctoral thesis, the author outlines its limitations and point at directions for future research. These mainly address providing further evidence on the long-term performance effects of organizational misconduct, enriching our knowledge on further cognitive biases eventually leading to misconduct, and conceptualizing nudging beyond the use-case of workplace sexual harassment.
The computational analysis and the optimization of transport and mixing processes in fluid flows are of ongoing scientific interest. Transfer operator methods are powerful tools for the study of these processes in dynamical systems. The focus in this context has been mostly on closed dynamical systems and the main applications have been geophysical flows. In this thesis, the authors consider transport and mixing in closed flow systems and in open flow systems that mimic technical mixing devices. Via transfer operator methods, They study the coherent behavior in closed example systems including a turbulent Rayleigh-Bénard convection flow and consider the finite-time mixing of two fluids. They extend the transfer operator framework to specific open flows. In particular, they study time-periodic open flow systems with constant inflow and outflow of fluid particles and consider several example systems. In this case, the transfer operator is represented by a transition matrix of a time-homogeneous absorbing Markov chain restricted to finite transient states. The chaotic saddle and its stable and unstable manifolds organize the transport processes in open systems. The authors extract these structures directly from leading eigenvectors of the transition matrix. For a constant source of two fluids in different colors, the mass distribution in the mixer and its outlet region converges to an invariant mixing pattern. In parameter studies, they quantify the degree of mixing of the resulting patterns by several mixing measures. More recently, network-based methods that construct graphs on trajectories of fluid particles have been developed to study coherent behavior in fluid flow. They use a method based on diffusion maps to extract organizing structures in open example systems directly from trajectories of fluid particles and extend this method to describe the mixing of two types of fluids.
This study examines the perspective of German venture capitalists on the success factors of digital startups and follows an explorative three-dimensional research approach that integrates the micro perspective on the entrepreneurial personality, the macro perspective on the entrepreneurial context, and the meso perspective on the business model. Thus, the study operates in a very young field of entrepreneurship research. One of the purposes of this research project is to work out the significance of particular characteristics at each research level for the economic success of a digital start-up from the perspective of German venture capitalists. Furthermore, the study sheds light on the view of this group of experts on the relevance of an entire group of characteristics. To answer the central research questions, qualitative research methods and a mixed-methods approach are pursued, with quantitative and qualitative primary data being collected by means of theory-driven semi-structured expert interviews. As a result, a total of four articles have been produced: three articles that focus on presenting the results of qualitative research from only one of the three aforementioned research perspectives each, and a fourth article that combines methods from qualitative and quantitative research and derives an integrated, evidence-based working model of the economic success of digital startups from the perspective of German venture capital (VC) investors.
The requirements for the design of information and assistance systems in labour-intensive processes are interdisciplinary and have not yet been sufficiently addressed in research. This dissertation analyses, evaluates and describes possibilities for increasing the effectiveness and efficiency of labour-intensive processes through design-optimised socio-technical systems. The work thus contributes to further developing information and assistance systems for industrial applications and use in healthcare. The central dimensions of people, activity, context and technology are the focus of the scientific investigations following the Design Science Research paradigm. Design principles derived from this, a corresponding taxonomy, and a conceptual reference model for the design of socio-technical systems are the results of this dissertation.
This cumulative dissertation presents how commercial banks in Germany communicate their ambitions and commitment regarding corporate responsibility - i.e., CSR. The results of the first article show that the quality of mandatory non-financial reporting needs to be improved and that certain characteristics (e.g., previous reporting experience, reporting format and standard) have a positive influence on reporting quality. The second article shows that the CSR reporting scope on bank websites also has room for improvement and that various banking characteristics such as size, capital market orientation, media visibility or public ownership have an influence on communication. The third article illustrates that credit institutions in Germany are increasingly using social media for CSR communication, but that CSR communication strategies differ (Facebook vs. Twitter). The fourth article discusses CSR communication using advertisements and shows that the conceptual design of advertisements should be in line with the credit institution's business model and is therefore beneficial.
Artificial intelligence, most prominently in the form of machine learning, is shaping up to be one of the most transformational technologies of the 21st century. Auditors are among the professions forecasted to be the most affected by artificial intelligence, as the profession encompasses many highly structured and repetitive tasks. Automating such tasks would naturally increase the efficiency of financial statement audits. By allowing auditors to focus on higher value-added tasks, and the capability to analyze large volumes of data at a fracture of the time a human would need, artificial intelligence would also benefit the effectiveness of auditing. Despite these benefits, to this day, the actual adoption of artificial intelligence in the audit domain remains rather limited. The audit profession is highly regulated and has to consider requirements regarding, e.g. the application of professional standards, codes of conduct, and data protection obligations. Hence, the question arises of how audit firms can be supported in their efforts to adopt artificial intelligence and how machine learning systems can be designed to comply with the specific demands of the audit domain. The goal of this dissertation is to better understand the adoption of artificial intelligence in the audit domain and to actively support the adoption of artificial intelligence in auditing based on this understanding. To this end, we employ a mixture of research methods. On the one hand, the research presented here adopts a qualitative approach, examining the adoption of artificial intelligence and other advanced analytical technologies of the audit domain through taxonomy development and grounded theory. The findings of these studies inspire the second stream of work within this dissertation, which adopts a quantitative and design-oriented approach: It focuses on using machine learning to extract information from invoices for tests of details. Tests of details are essential substantive audit procedures used in nearly every audit. This dissertation proposes a new machine learning model architecture for information extraction from invoices, compares different machine learning models, and proposes design principles for machine learning pipelines for an audit application addressing the test of details through action design research.